過去數十年來，機器人技術的進步已將各種功能型機器人帶至我們的家中，現今，人們對於智慧型服務用機器人之需求預期將會增加。本論文的目標為設計一機械手臂來使服務用機器人能遞送物件，且提出一具有以行為基礎之看而後動架構之視覺導引控制策略，來抓取所需遞送之物件。本研究利用一個未經校準的眼在手視覺系統來提供視覺資料，用以控制手臂進行目標物之抓取。此策略是基於兩個預先定義的影像特徵，在類神經模糊控制器之設計中，每個影像特徵透過定義特定視覺行為之模糊規則，直覺式地決定相對於攝影機座標的一個自由度運動。藉由整合移動平台逼近階段之行為及機械手臂微調階段之行為，依序執行抓取工作。最後，實驗顯示出所提出之控制策略能用以實現在移動式機械手臂上，以逼近目標物且精確地定位其夾爪來抓取物件。

Over the last decades, progress in the robot technology has brought various functional robots to our homes’ doorsteps. Nowadays, it is also expected that the demand of the intelligent service robots will be increased. The objective of this thesis is to design a robot manipulator for a service robot to transfer material and propose a vision-guided control strategy with a behavior-based look-and-move structure to grasp the object to be transferred. This study utilizes an uncalibrated eye-in-hand vision system to provide visual information for controlling the manipulator to grasp the target object. The strategy is based on two predefined image features. In the designed neural fuzzy controllers, each image feature is taken to generate intuitively one degree of freedom motion command relative to the camera coordinate frame using fuzzy rules, which define a particular visual behavior. The behaviors in the approaching stage of the mobile base and in the positioning stage of the robot manipulator are then combined and executed sequentially to perform grasping tasks. Finally, the proposed control strategy is experimentally applied to realize a mobile manipulator that can approach a target object and precisely position its gripper to grasp the object.

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